Remove Hybrid AI Remove Natural Language Processing Remove NLP
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Bigger isn’t always better: How hybrid AI pattern enables smaller language models

IBM Journey to AI blog

However, there are smaller models that have the potential to innovate gen AI capabilities on mobile devices. Let’s examine these solutions from the perspective of a hybrid AI model. The basics of LLMs LLMs are a special class of AI models powering this new paradigm. Is hybrid AI the answer?

Hybrid AI 246
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AI Learns from AI: The Emergence of Social Learning Among Large Language Models

Unite.AI

Since OpenAI unveiled ChatGPT in late 2022, the role of foundational large language models (LLMs) has become increasingly prominent in artificial intelligence (AI), particularly in natural language processing (NLP).

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AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the difference?

IBM Journey to AI blog

Categories of AI Three main categories of AI are: Artificial Narrow Intelligence (ANI) Artificial General Intelligence (AGI) Artificial Super Intelligence (ASI) ANI is considered “weak” AI, whereas the other two types are classified as “strong” AI.

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A Guide to Mastering Large Language Models

Unite.AI

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. Their foundational nature allows them to be fine-tuned for a wide variety of downstream NLP tasks. This enables pretraining at scale.

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Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available

AWS Machine Learning Blog

With eight Qualcomm AI 100 Standard accelerators and 128 GiB of total accelerator memory, customers can also use DL2q instances to run popular generative AI applications, such as content generation, text summarization, and virtual assistants, as well as classic AI applications for natural language processing and computer vision.

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Unbundling the Graph in GraphRAG

O'Reilly Media

See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., at Google, and “ Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks ” by Patrick Lewis, et al., at Facebook—both from 2020. Here’s a simple rough sketch of RAG: Start with a collection of documents about a domain.

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Evaluation Derangement Syndrome (EDS) in the GPU-poor’s GenAI. Part 1: the case for Evaluation-Driven Development

deepsense.ai

This disruptive tendency manifests every few months and shows no sign of slowing down, with the recent releases of Llama 2 [25] and Mistral [26] (the great hopes of open source NLP [27, 28]) and two proprietary game-changers seemingly just around the corner: Gemini [29] and GPT-5 [30]. Galstyan A. Cresswell J.C., Hosseinzadeh R. Alnajjar K.,